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Organizar recursos con etiquetas

En este documento se explica cómo usar etiquetas para organizar los recursos de Batch.

Las etiquetas son pares clave-valor que se aplican a los recursos para agruparlos y describirlos. Batch tiene etiquetas predefinidas, que se aplican automáticamente a los recursos, y etiquetas personalizadas, que puedes definir y aplicar al crear un trabajo.

Las etiquetas te permiten filtrar los resultados de las listas de recursos y los informes de facturación de Cloud. Por ejemplo, puedes usar etiquetas para hacer lo siguiente:

Clarifica y organiza la lista de tareas de tu proyecto.
Distingue los elementos ejecutables de un trabajo mediante etiquetas que describan el tipo de contenedor o secuencia de comandos que especifican.
Analiza los costes filtrando los informes de facturación de Cloud por los recursos creados por Batch o por tareas específicas.

Para obtener más información sobre las etiquetas, consulta la documentación de Compute Engine sobre etiquetas.

Antes de empezar

Si no has usado Batch antes, consulta el artículo Empezar a usar Batch y habilita Batch completando los requisitos previos para proyectos y usuarios.
Para obtener los permisos que necesitas para crear un trabajo, pide a tu administrador que te conceda los siguientes roles de gestión de identidades y accesos:
- Editor de trabajos por lotes (roles/batch.jobsEditor) en el proyecto
- Usuario de cuenta de servicio (roles/iam.serviceAccountUser) en la cuenta de servicio del trabajo, que de forma predeterminada es la cuenta de servicio predeterminada de Compute Engine
Para obtener más información sobre cómo conceder roles, consulta el artículo Gestionar el acceso a proyectos, carpetas y organizaciones.

También puedes conseguir los permisos necesarios a través de roles personalizados u otros roles predefinidos.

Restricciones

Además de los requisitos de las etiquetas especificados en la documentación de Compute Engine, aplicar etiquetas a un trabajo por lotes y a sus recursos tiene las siguientes restricciones:

Batch solo admite etiquetas de recursos que se hayan creado con Batch y que sean de los siguientes tipos:
- Empleo
- Ejecutables
- Unidades de procesamiento gráfico (GPUs) de un trabajo (si las hay)
- Discos persistentes (discos de arranque y cualquier volumen de almacenamiento) de un trabajo
- Instancias de máquina virtual (VM) de un trabajo
Después de tener en cuenta las etiquetas predefinidas que Batch aplica automáticamente a una tarea, puedes definir las siguientes cantidades de etiquetas personalizadas:
- Puedes definir un máximo de 63 etiquetas personalizadas para aplicarlas a la tarea y a sus elementos ejecutables.
- Puedes definir un máximo de 61 etiquetas personalizadas para aplicar a cada GPU, disco persistente y VM creados para el trabajo.
Batch solo permite definir etiquetas personalizadas con nombres únicos. Esto tiene las siguientes consecuencias:
- Si intenta anular una etiqueta predefinida, se producirán errores.
- Si define una etiqueta personalizada duplicada, se sobrescribirá la etiqueta personalizada ya creada.
Batch solo admite la definición de etiquetas al crear un trabajo.
- No se pueden añadir, actualizar ni quitar etiquetas de los trabajos y los elementos ejecutables.
- Aunque es posible usar Compute Engine para añadir, actualizar o quitar etiquetas de los discos persistentes y las VMs creados para los trabajos, no se recomienda. No se puede estimar de forma fiable el periodo durante el que existen los recursos de un trabajo y es posible que los cambios no funcionen correctamente con Batch.
Para usar etiquetas y filtrar la lista de tareas, debes ver la lista de tareas con gcloud CLI o la API Batch.

Etiquetas predefinidas

Cada etiqueta predefinida tiene una clave que empieza por el prefijo batch-. De forma predeterminada, Batch aplica automáticamente las siguientes etiquetas predefinidas:

En cada trabajo que crees:
- batch-job-id: el valor de esta etiqueta es el nombre del trabajo.
A cada GPU, disco persistente y VM creados para un trabajo:
- batch-job-id: el valor de esta etiqueta es el nombre del trabajo.
- batch-job-uid: el valor de esta etiqueta es el identificador único (UID) del trabajo.
- batch-node: el valor de esta etiqueta es nulo. Solo agrupa todas las GPUs, los discos persistentes y las VMs que se crean para los trabajos. Por ejemplo, usa esta etiqueta cuando consultes un informe de Facturación de Cloud para identificar los costes de todas las GPUs, los discos persistentes y las VMs creados por Batch.

Definir etiquetas personalizadas

Cuando creas un trabajo, puedes definir una o varias etiquetas personalizadas. Puedes definir etiquetas personalizadas con claves nuevas o con claves que ya use tu proyecto. Para definir etiquetas personalizadas, selecciona uno o varios de los siguientes métodos de este documento en función del propósito de la etiqueta:

Define etiquetas personalizadas para el trabajo y sus recursos.

En esta sección se explica cómo aplicar una o varias etiquetas personalizadas al trabajo y a cada GPU, disco persistente y VM creados para el trabajo. Una vez creada la tarea, puedes usar estas etiquetas para filtrar los informes de facturación de Cloud y las listas de tareas, discos persistentes y VMs de tu proyecto.

Nota: Los discos persistentes y las VMs creados para un trabajo solo aparecen en las listas de tu proyecto durante el tiempo de ejecución del trabajo (después de crearse y antes de eliminarse).
Defina etiquetas personalizadas para el trabajo.

En esta sección se explica cómo aplicar una o varias etiquetas personalizadas al trabajo. Después de crear el trabajo, puedes usar estas etiquetas para filtrar las listas de trabajos de tu proyecto.
Define etiquetas personalizadas para elementos ejecutables.

En esta sección se explica cómo aplicar una o varias etiquetas personalizadas a una o varias tareas ejecutables del trabajo. Una vez que hayas creado el trabajo, podrás usar estas etiquetas para filtrar las listas de trabajos de tu proyecto.

Definir etiquetas personalizadas para el trabajo y sus recursos

Las etiquetas definidas en el campo labels de la política de asignación de una tarea se aplican a la tarea, así como a cada GPU (si la hay), disco persistente (todos los discos de arranque y los volúmenes de almacenamiento nuevos) y VM creados para la tarea.

Puedes definir etiquetas para un trabajo y sus recursos al crear un trabajo con la CLI de gcloud o la API Batch.

gcloud

Por ejemplo, para crear un trabajo de contenedor básico en us-central1 que defina dos etiquetas personalizadas que se apliquen al trabajo y a los recursos creados para el trabajo, sigue estos pasos:

Crea un archivo JSON que especifique los detalles de configuración del trabajo y el campo allocationPolicy.labels.

{
  "allocationPolicy": {
    "instances": [
      {
        "policy": {
          "machineType": "e2-standard-4"
        }
      }
    ],
    "labels": {
      "VM_LABEL_NAME1": "VM_LABEL_VALUE1",
      "VM_LABEL_NAME2": "VM_LABEL_VALUE2"
    }
  },
  "taskGroups": [
    {
      "taskSpec": {
        "runnables": [
          {
            "container": {
              "imageUri": "gcr.io/google-containers/busybox",
              "entrypoint": "/bin/sh",
              "commands": [
                "-c",
                "echo Hello world!"
              ]
            }
          }
        ]
      }
    }
  ]
}

Haz los cambios siguientes:

VM_LABEL_NAME1: nombre de la primera etiqueta que se aplicará a las VMs creadas para el trabajo.
VM_LABEL_VALUE1: el valor de la primera etiqueta que se aplicará a las VMs creadas para el trabajo.
VM_LABEL_NAME2: Nombre de la segunda etiqueta que se aplicará a las VMs creadas para el trabajo.
VM_LABEL_VALUE2: valor de la segunda etiqueta que se aplicará a las VMs creadas para el trabajo.

Crea el trabajo en us-central1 con el comando gcloud batch jobs submit.
```
gcloud batch jobs submit example-job \
    --config=JSON_CONFIGURATION_FILE \
    --location=us-central1
```
Sustituye JSON_CONFIGURATION_FILE por la ruta al archivo JSON con los detalles de configuración del trabajo que has creado en el paso anterior.

API

Por ejemplo, para crear una tarea de contenedor básica en us-central1 que defina dos etiquetas personalizadas que se apliquen a la tarea y a los recursos creados para la tarea, haz una solicitud POST al método jobs.create y especifica el campo allocationPolicy.labels.

POST https://batch.googleapis.com/v1/projects/example-project/locations/us-central1/jobs?job_id=example-job

{
  "allocationPolicy": {
    "instances": [
      {
        "policy": {
          "machineType": "e2-standard-4"
        }
      }
    ],
    "labels": {
      "VM_LABEL_NAME1": "VM_LABEL_VALUE1",
      "VM_LABEL_NAME2": "VM_LABEL_VALUE2"
    }
  },
  "taskGroups": [
    {
      "taskSpec": {
        "runnables": [
          {
            "container": {
              "imageUri": "gcr.io/google-containers/busybox",
              "entrypoint": "/bin/sh",
              "commands": [
                "-c",
                "echo Hello world!"
              ]
            }
          }
        ]
      }
    }
  ]
}

Haz los cambios siguientes:

VM_LABEL_NAME1: nombre de la primera etiqueta que se aplicará a las VMs creadas para el trabajo.
VM_LABEL_VALUE1: valor de la primera etiqueta que se aplicará a las VMs creadas para el trabajo.
VM_LABEL_NAME2: nombre de la segunda etiqueta que se aplicará a las VMs creadas para el trabajo.
VM_LABEL_VALUE2: valor de la segunda etiqueta que se aplicará a las VMs creadas para el trabajo.

Java


import com.google.cloud.batch.v1.AllocationPolicy;
import com.google.cloud.batch.v1.BatchServiceClient;
import com.google.cloud.batch.v1.ComputeResource;
import com.google.cloud.batch.v1.CreateJobRequest;
import com.google.cloud.batch.v1.Job;
import com.google.cloud.batch.v1.LogsPolicy;
import com.google.cloud.batch.v1.Runnable;
import com.google.cloud.batch.v1.TaskGroup;
import com.google.cloud.batch.v1.TaskSpec;
import com.google.protobuf.Duration;
import java.io.IOException;
import java.util.concurrent.ExecutionException;
import java.util.concurrent.TimeUnit;
import java.util.concurrent.TimeoutException;

public class CreateBatchAllocationPolicyLabel {

  public static void main(String[] args)
      throws IOException, ExecutionException, InterruptedException, TimeoutException {
    // TODO(developer): Replace these variables before running the sample.
    // Project ID or project number of the Google Cloud project you want to use.
    String projectId = "YOUR_PROJECT_ID";
    // Name of the region you want to use to run the job. Regions that are
    // available for Batch are listed on: https://cloud.google.com/batch/docs/get-started#locations
    String region = "us-central1";
    // The name of the job that will be created.
    // It needs to be unique for each project and region pair.
    String jobName = "example-job";
    // Name of the label1 to be applied for your Job.
    String labelName1 = "VM_LABEL_NAME1";
    // Value for the label1 to be applied for your Job.
    String labelValue1 = "VM_LABEL_VALUE1";
    // Name of the label2 to be applied for your Job.
    String labelName2 = "VM_LABEL_NAME2";
    // Value for the label2 to be applied for your Job.
    String labelValue2 = "VM_LABEL_VALUE2";

    createBatchAllocationPolicyLabel(projectId, region, jobName, labelName1,
        labelValue1, labelName2, labelValue2);
  }

  // This method shows how to create a job with labels defined 
  // in the labels field of a job's allocation policy. These are 
  // applied to the job, as well as to each GPU (if any), persistent disk 
  // (all boot disks and any new storage volumes), and VM created for the job.
  public static Job createBatchAllocationPolicyLabel(String projectId, String region,
                               String jobName, String labelName1,
                               String labelValue1, String labelName2, String labelValue2)
      throws IOException, ExecutionException, InterruptedException, TimeoutException {
    // Initialize client that will be used to send requests. This client only needs to be created
    // once, and can be reused for multiple requests.
    try (BatchServiceClient batchServiceClient = BatchServiceClient.create()) {

      // Define what will be done as part of the job.
      Runnable runnable =
          Runnable.newBuilder()
              .setContainer(
                  Runnable.Container.newBuilder()
                      .setImageUri("gcr.io/google-containers/busybox")
                      .setEntrypoint("/bin/sh")
                      .addCommands("-c")
                      .addCommands(
                          "echo Hello world! This is task ${BATCH_TASK_INDEX}. "
                              + "This job has a total of ${BATCH_TASK_COUNT} tasks.")
                      .build())
              .build();

      // We can specify what resources are requested by each task.
      ComputeResource computeResource =
          ComputeResource.newBuilder()
              // In milliseconds per cpu-second. This means the task requires 50% of a single CPUs.
              .setCpuMilli(2000)
              // In MiB.
              .setMemoryMib(2000)
              .build();

      TaskSpec task =
          TaskSpec.newBuilder()
              // Jobs can be divided into tasks. In this case, we have only one task.
              .addRunnables(runnable)
              .setComputeResource(computeResource)
              .setMaxRetryCount(2)
              .setMaxRunDuration(Duration.newBuilder().setSeconds(3600).build())
              .build();

      // Tasks are grouped inside a job using TaskGroups.
      // Currently, it's possible to have only one task group.
      TaskGroup taskGroup = TaskGroup.newBuilder().setTaskCount(1).setTaskSpec(task).build();

      // Policies are used to define on what kind of virtual machines the tasks will run on.
      // In this case, we tell the system to use "e2-standard-4" machine type.
      // Read more about machine types here: https://cloud.google.com/compute/docs/machine-types
      AllocationPolicy.InstancePolicy instancePolicy =
          AllocationPolicy.InstancePolicy.newBuilder().setMachineType("e2-standard-4").build();

      AllocationPolicy allocationPolicy =
          AllocationPolicy.newBuilder()
              .addInstances(AllocationPolicy.InstancePolicyOrTemplate.newBuilder()
                  .setPolicy(instancePolicy)
                  .build())
              // Labels and their value to be applied to the job and its resources
              .putLabels(labelName1, labelValue1)
              .putLabels(labelName2, labelValue2)
              .build();

      Job job =
          Job.newBuilder()
              .addTaskGroups(taskGroup)
              .setAllocationPolicy(allocationPolicy)
              // We use Cloud Logging as it's an out of the box available option.
              .setLogsPolicy(LogsPolicy.newBuilder()
                      .setDestination(LogsPolicy.Destination.CLOUD_LOGGING).build())
              .build();

      CreateJobRequest createJobRequest =
          CreateJobRequest.newBuilder()
              // The job's parent is the region in which the job will run.
              .setParent(String.format("projects/%s/locations/%s", projectId, region))
              .setJob(job)
              .setJobId(jobName)
              .build();

      Job result =
          batchServiceClient
              .createJobCallable()
              .futureCall(createJobRequest)
              .get(5, TimeUnit.MINUTES);

      System.out.printf("Successfully created the job: %s", result.getName());

      return result;
    }
  }

}

Node.js

// Imports the Batch library
const batchLib = require('@google-cloud/batch');
const batch = batchLib.protos.google.cloud.batch.v1;

// Instantiates a client
const batchClient = new batchLib.v1.BatchServiceClient();

/**
 * TODO(developer): Update these variables before running the sample.
 */
// Project ID or project number of the Google Cloud project you want to use.
const projectId = await batchClient.getProjectId();
// Name of the region you want to use to run the job. Regions that are
// available for Batch are listed on: https://cloud.google.com/batch/docs/get-started#locations
const region = 'europe-central2';
// The name of the job that will be created.
// It needs to be unique for each project and region pair.
const jobName = 'batch-labels-allocation-job';
// Name of the label1 to be applied for your Job.
const labelName1 = 'vm_label_name_1';
// Value for the label1 to be applied for your Job.
const labelValue1 = 'vmLabelValue1';
// Name of the label2 to be applied for your Job.
const labelName2 = 'vm_label_name_2';
// Value for the label2 to be applied for your Job.
const labelValue2 = 'vmLabelValue2';

// Define what will be done as part of the job.
const runnable = new batch.Runnable({
  script: new batch.Runnable.Script({
    commands: ['-c', 'echo Hello world! This is task ${BATCH_TASK_INDEX}.'],
  }),
});

// Specify what resources are requested by each task.
const computeResource = new batch.ComputeResource({
  // In milliseconds per cpu-second. This means the task requires 50% of a single CPUs.
  cpuMilli: 500,
  // In MiB.
  memoryMib: 16,
});

const task = new batch.TaskSpec({
  runnables: [runnable],
  computeResource,
  maxRetryCount: 2,
  maxRunDuration: {seconds: 3600},
});

// Tasks are grouped inside a job using TaskGroups.
const group = new batch.TaskGroup({
  taskCount: 3,
  taskSpec: task,
});

// Policies are used to define on what kind of virtual machines the tasks will run on.
// In this case, we tell the system to use "e2-standard-4" machine type.
// Read more about machine types here: https://cloud.google.com/compute/docs/machine-types
const instancePolicy = new batch.AllocationPolicy.InstancePolicy({
  machineType: 'e2-standard-4',
});

const allocationPolicy = new batch.AllocationPolicy({
  instances: [{policy: instancePolicy}],
});
// Labels and their value to be applied to the job and its resources.
allocationPolicy.labels[labelName1] = labelValue1;
allocationPolicy.labels[labelName2] = labelValue2;

const job = new batch.Job({
  name: jobName,
  taskGroups: [group],
  labels: {env: 'testing', type: 'script'},
  allocationPolicy,
  // We use Cloud Logging as it's an option available out of the box
  logsPolicy: new batch.LogsPolicy({
    destination: batch.LogsPolicy.Destination.CLOUD_LOGGING,
  }),
});

// The job's parent is the project and region in which the job will run
const parent = `projects/${projectId}/locations/${region}`;

async function callCreateBatchLabelsAllocation() {
  // Construct request
  const request = {
    parent,
    jobId: jobName,
    job,
  };

  // Run request
  const [response] = await batchClient.createJob(request);
  console.log(JSON.stringify(response));
}

await callCreateBatchLabelsAllocation();

Python

from google.cloud import batch_v1


def create_job_with_custom_allocation_policy_labels(
    project_id: str, region: str, job_name: str, labels: dict
) -> batch_v1.Job:
    """
    This method shows the creation of a Batch job with custom labels which describe the allocation policy.
    Args:
        project_id (str): project ID or project number of the Cloud project you want to use.
        region (str): name of the region you want to use to run the job. Regions that are
            available for Batch are listed on: https://cloud.google.com/batch/docs/locations
        job_name (str): the name of the job that will be created.
        labels (dict): a dictionary of key-value pairs that will be used as labels
            E.g., {"label_key1": "label_value2", "label_key2": "label_value2"}
    Returns:
        batch_v1.Job: The created Batch job object containing configuration details.
    """
    client = batch_v1.BatchServiceClient()

    runnable = batch_v1.Runnable()
    runnable.container = batch_v1.Runnable.Container()
    runnable.container.image_uri = "gcr.io/google-containers/busybox"
    runnable.container.entrypoint = "/bin/sh"
    runnable.container.commands = [
        "-c",
        "echo Hello world!",
    ]

    # Create a task specification and assign the runnable and volume to it
    task = batch_v1.TaskSpec()
    task.runnables = [runnable]

    # Specify what resources are requested by each task.
    resources = batch_v1.ComputeResource()
    resources.cpu_milli = 2000  # in milliseconds per cpu-second. This means the task requires 2 whole CPUs.
    resources.memory_mib = 16  # in MiB
    task.compute_resource = resources

    task.max_retry_count = 2
    task.max_run_duration = "3600s"

    # Create a task group and assign the task specification to it
    group = batch_v1.TaskGroup()
    group.task_count = 3
    group.task_spec = task

    # Policies are used to define on what kind of virtual machines the tasks will run on.
    # In this case, we tell the system to use "e2-standard-4" machine type.
    # Read more about machine types here: https://cloud.google.com/compute/docs/machine-types
    policy = batch_v1.AllocationPolicy.InstancePolicy()
    policy.machine_type = "e2-standard-4"
    instances = batch_v1.AllocationPolicy.InstancePolicyOrTemplate()
    instances.policy = policy
    allocation_policy = batch_v1.AllocationPolicy()
    allocation_policy.instances = [instances]

    # Assign the provided labels to the allocation policy
    allocation_policy.labels = labels

    # Create the job and assign the task group and allocation policy to it
    job = batch_v1.Job()
    job.task_groups = [group]
    job.allocation_policy = allocation_policy

    # We use Cloud Logging as it's an out of the box available option
    job.logs_policy = batch_v1.LogsPolicy()
    job.logs_policy.destination = batch_v1.LogsPolicy.Destination.CLOUD_LOGGING

    # Create the job request and set the job and job ID
    create_request = batch_v1.CreateJobRequest()
    create_request.job = job
    create_request.job_id = job_name
    # The job's parent is the region in which the job will run
    create_request.parent = f"projects/{project_id}/locations/{region}"

    return client.create_job(create_request)

Definir etiquetas personalizadas para el trabajo

Las etiquetas definidas en el campo labels de la tarea solo se aplican a la tarea.

Puedes definir etiquetas para una tarea al crearla con la CLI de gcloud o la API Batch.

gcloud

Por ejemplo, para crear un trabajo de contenedor básico en us-central1 que defina dos etiquetas personalizadas que se apliquen al propio trabajo, sigue estos pasos:

Crea un archivo JSON que especifique los detalles de configuración del trabajo y el campo labels.

{
  "taskGroups": [
    {
      "taskSpec": {
        "runnables": [
          {
            "container": {
              "imageUri": "gcr.io/google-containers/busybox",
              "entrypoint": "/bin/sh",
              "commands": [
                "-c",
                "echo Hello World!"
              ]
            }
          }
        ]
      }
    }
  ],
  "labels": {
    "JOB_LABEL_NAME1": "JOB_LABEL_VALUE1",
    "JOB_LABEL_NAME2": "JOB_LABEL_VALUE2"
  }
}

Haz los cambios siguientes:

JOB_LABEL_NAME1: el nombre de la primera etiqueta que se aplicará al trabajo.
JOB_LABEL_VALUE1: El valor de la primera etiqueta que se aplicará al trabajo.
JOB_LABEL_NAME2: el nombre de la segunda etiqueta que quieres aplicar al trabajo.
JOB_LABEL_VALUE2: el valor de la segunda etiqueta que se va a aplicar al trabajo.

Crea el trabajo en us-central1 con el comando gcloud batch jobs submit y las siguientes marcas:
```
gcloud batch jobs submit example-job \
    --config=JSON_CONFIGURATION_FILE \
    --location=us-central1
```
Sustituye JSON_CONFIGURATION_FILE por la ruta al archivo JSON con los detalles de configuración del trabajo que has creado en el paso anterior.

API

Por ejemplo, para crear un trabajo de contenedor en us-central1 que defina dos etiquetas personalizadas que se aplicarán al propio trabajo, haz una solicitud POST al método jobs.create y especifica el campo labels.

POST https://batch.googleapis.com/v1/projects/example-project/locations/us-central1/jobs?job_id=example-job

{
  "taskGroups": [
    {
      "taskSpec": {
        "runnables": [
          {
            "container": {
              "imageUri": "gcr.io/google-containers/busybox",
              "entrypoint": "/bin/sh",
              "commands": [
                "-c",
                "echo Hello World!"
              ]
            }
          }
        ]
      }
    }
  ],
  "labels": {
    "JOB_LABEL_NAME1": "JOB_LABEL_VALUE1",
    "JOB_LABEL_NAME2": "JOB_LABEL_VALUE2"
  }
}

Haz los cambios siguientes:

JOB_LABEL_NAME1: el nombre de la primera etiqueta que se aplicará al trabajo.
JOB_LABEL_VALUE1: el valor de la primera etiqueta que se va a aplicar a tu trabajo.
JOB_LABEL_NAME2: nombre de la segunda etiqueta que se aplicará al trabajo.
JOB_LABEL_VALUE2: el valor de la segunda etiqueta que se va a aplicar al trabajo.

Java


import com.google.cloud.batch.v1.BatchServiceClient;
import com.google.cloud.batch.v1.ComputeResource;
import com.google.cloud.batch.v1.CreateJobRequest;
import com.google.cloud.batch.v1.Job;
import com.google.cloud.batch.v1.LogsPolicy;
import com.google.cloud.batch.v1.Runnable;
import com.google.cloud.batch.v1.TaskGroup;
import com.google.cloud.batch.v1.TaskSpec;
import com.google.protobuf.Duration;
import java.io.IOException;
import java.util.concurrent.ExecutionException;
import java.util.concurrent.TimeUnit;
import java.util.concurrent.TimeoutException;


public class CreateBatchLabelJob {

  public static void main(String[] args)
      throws IOException, ExecutionException, InterruptedException, TimeoutException {
    // TODO(developer): Replace these variables before running the sample.
    // Project ID or project number of the Google Cloud project you want to use.
    String projectId = "YOUR_PROJECT_ID";
    // Name of the region you want to use to run the job. Regions that are
    // available for Batch are listed on: https://cloud.google.com/batch/docs/get-started#locations
    String region = "us-central1";
    // The name of the job that will be created.
    // It needs to be unique for each project and region pair.
    String jobName = "example-job";
    // Name of the label1 to be applied for your Job.
    String labelName1 = "JOB_LABEL_NAME1";
    // Value for the label1 to be applied for your Job.
    String labelValue1 = "JOB_LABEL_VALUE1";
    // Name of the label2 to be applied for your Job.
    String labelName2 = "JOB_LABEL_NAME2";
    // Value for the label2 to be applied for your Job.
    String labelValue2 = "JOB_LABEL_VALUE2";

    createBatchLabelJob(projectId, region, jobName, labelName1,
        labelValue1, labelName2, labelValue2);
  }

  // Creates a job with labels defined in the labels field.
  public static Job createBatchLabelJob(String projectId, String region, String jobName,
                    String labelName1, String labelValue1, String labelName2, String labelValue2)
      throws IOException, ExecutionException, InterruptedException, TimeoutException {
    // Initialize client that will be used to send requests. This client only needs to be created
    // once, and can be reused for multiple requests.
    try (BatchServiceClient batchServiceClient = BatchServiceClient.create()) {

      // Define what will be done as part of the job.
      Runnable runnable =
          Runnable.newBuilder()
              .setContainer(
                  Runnable.Container.newBuilder()
                      .setImageUri("gcr.io/google-containers/busybox")
                      .setEntrypoint("/bin/sh")
                      .addCommands("-c")
                      .addCommands(
                          "echo Hello world! This is task ${BATCH_TASK_INDEX}. "
                              + "This job has a total of ${BATCH_TASK_COUNT} tasks.")
                      .build())
              .build();

      // We can specify what resources are requested by each task.
      ComputeResource computeResource =
          ComputeResource.newBuilder()
              // In milliseconds per cpu-second. This means the task requires 50% of a single CPUs.
              .setCpuMilli(2000)
              // In MiB.
              .setMemoryMib(2000)
              .build();

      TaskSpec task =
          TaskSpec.newBuilder()
              // Jobs can be divided into tasks. In this case, we have only one task.
              .addRunnables(runnable)
              .setComputeResource(computeResource)
              .setMaxRetryCount(2)
              .setMaxRunDuration(Duration.newBuilder().setSeconds(3600).build())
              .build();

      // Tasks are grouped inside a job using TaskGroups.
      // Currently, it's possible to have only one task group.
      TaskGroup taskGroup = TaskGroup.newBuilder().setTaskCount(1).setTaskSpec(task).build();

      Job job =
          Job.newBuilder()
              .addTaskGroups(taskGroup)
              // We use Cloud Logging as it's an out of the box available option.
              .setLogsPolicy(LogsPolicy.newBuilder()
              .setDestination(LogsPolicy.Destination.CLOUD_LOGGING).build())
              // Labels and their value to be applied to the job.
              .putLabels(labelName1, labelValue1)
              .putLabels(labelName2, labelValue2)
              .build();

      CreateJobRequest createJobRequest =
          CreateJobRequest.newBuilder()
              // The job's parent is the region in which the job will run.
              .setParent(String.format("projects/%s/locations/%s", projectId, region))
              .setJob(job)
              .setJobId(jobName)
              .build();

      Job result =
          batchServiceClient
              .createJobCallable()
              .futureCall(createJobRequest)
              .get(5, TimeUnit.MINUTES);

      System.out.printf("Successfully created the job: %s", result.getName());

      return result;
    }
  }

}

Node.js

// Imports the Batch library
const batchLib = require('@google-cloud/batch');
const batch = batchLib.protos.google.cloud.batch.v1;

// Instantiates a client
const batchClient = new batchLib.v1.BatchServiceClient();

/**
 * TODO(developer): Update these variables before running the sample.
 */
// Project ID or project number of the Google Cloud project you want to use.
const projectId = await batchClient.getProjectId();
// Name of the region you want to use to run the job. Regions that are
// available for Batch are listed on: https://cloud.google.com/batch/docs/get-started#locations
const region = 'europe-central2';
// The name of the job that will be created.
// It needs to be unique for each project and region pair.
const jobName = 'batch-labels-job';
// Name of the label1 to be applied for your Job.
const labelName1 = 'job_label_name_1';
// Value for the label1 to be applied for your Job.
const labelValue1 = 'job_label_value1';
// Name of the label2 to be applied for your Job.
const labelName2 = 'job_label_name_2';
// Value for the label2 to be applied for your Job.
const labelValue2 = 'job_label_value2';

// Define what will be done as part of the job.
const runnable = new batch.Runnable({
  container: new batch.Runnable.Container({
    imageUri: 'gcr.io/google-containers/busybox',
    entrypoint: '/bin/sh',
    commands: ['-c', 'echo Hello world! This is task ${BATCH_TASK_INDEX}.'],
  }),
});

// Specify what resources are requested by each task.
const computeResource = new batch.ComputeResource({
  // In milliseconds per cpu-second. This means the task requires 50% of a single CPUs.
  cpuMilli: 500,
  // In MiB.
  memoryMib: 16,
});

const task = new batch.TaskSpec({
  runnables: [runnable],
  computeResource,
  maxRetryCount: 2,
  maxRunDuration: {seconds: 3600},
});

// Tasks are grouped inside a job using TaskGroups.
const group = new batch.TaskGroup({
  taskCount: 3,
  taskSpec: task,
});

const job = new batch.Job({
  name: jobName,
  taskGroups: [group],
  // We use Cloud Logging as it's an option available out of the box
  logsPolicy: new batch.LogsPolicy({
    destination: batch.LogsPolicy.Destination.CLOUD_LOGGING,
  }),
});

// Labels and their value to be applied to the job and its resources.
job.labels[labelName1] = labelValue1;
job.labels[labelName2] = labelValue2;

// The job's parent is the project and region in which the job will run
const parent = `projects/${projectId}/locations/${region}`;

async function callCreateBatchLabelsJob() {
  // Construct request
  const request = {
    parent,
    jobId: jobName,
    job,
  };

  // Run request
  const [response] = await batchClient.createJob(request);
  console.log(JSON.stringify(response));
}

await callCreateBatchLabelsJob();

Python

from google.cloud import batch_v1


def create_job_with_custom_job_labels(
    project_id: str,
    region: str,
    job_name: str,
    labels: dict,
) -> batch_v1.Job:
    """
    This method creates a Batch job with custom labels.
    Args:
        project_id (str): project ID or project number of the Cloud project you want to use.
        region (str): name of the region you want to use to run the job. Regions that are
            available for Batch are listed on: https://cloud.google.com/batch/docs/locations
        job_name (str): the name of the job that will be created.
        labels (dict): A dictionary of custom labels to be added to the job.
            E.g., {"label_key1": "label_value2", "label_key2": "label_value2"}
    Returns:
        batch_v1.Job: The created Batch job object containing configuration details.
    """
    client = batch_v1.BatchServiceClient()

    runnable = batch_v1.Runnable()
    runnable.container = batch_v1.Runnable.Container()
    runnable.container.image_uri = "gcr.io/google-containers/busybox"
    runnable.container.entrypoint = "/bin/sh"
    runnable.container.commands = [
        "-c",
        "echo Hello world!",
    ]

    # Create a task specification and assign the runnable and volume to it
    task = batch_v1.TaskSpec()
    task.runnables = [runnable]

    # Specify what resources are requested by each task.
    resources = batch_v1.ComputeResource()
    resources.cpu_milli = 2000  # in milliseconds per cpu-second. This means the task requires 2 whole CPUs.
    resources.memory_mib = 16  # in MiB
    task.compute_resource = resources

    task.max_retry_count = 2
    task.max_run_duration = "3600s"

    # Create a task group and assign the task specification to it
    group = batch_v1.TaskGroup()
    group.task_count = 3
    group.task_spec = task

    # Policies are used to define on what kind of virtual machines the tasks will run on.
    # In this case, we tell the system to use "e2-standard-4" machine type.
    # Read more about machine types here: https://cloud.google.com/compute/docs/machine-types
    policy = batch_v1.AllocationPolicy.InstancePolicy()
    policy.machine_type = "e2-standard-4"
    instances = batch_v1.AllocationPolicy.InstancePolicyOrTemplate()
    instances.policy = policy
    allocation_policy = batch_v1.AllocationPolicy()
    allocation_policy.instances = [instances]

    # Create the job and assign the task group and allocation policy to it
    job = batch_v1.Job()
    job.task_groups = [group]
    job.allocation_policy = allocation_policy

    # Set the labels for the job
    job.labels = labels

    # We use Cloud Logging as it's an out of the box available option
    job.logs_policy = batch_v1.LogsPolicy()
    job.logs_policy.destination = batch_v1.LogsPolicy.Destination.CLOUD_LOGGING

    # Create the job request and set the job and job ID
    create_request = batch_v1.CreateJobRequest()
    create_request.job = job
    create_request.job_id = job_name
    # The job's parent is the region in which the job will run
    create_request.parent = f"projects/{project_id}/locations/{region}"

    return client.create_job(create_request)

Definir etiquetas personalizadas para elementos ejecutables

Las etiquetas definidas en el campo labels de un elemento ejecutable solo se aplican a ese elemento.

Puedes definir etiquetas para uno o varios elementos ejecutables al crear un trabajo con la CLI de gcloud o la API Batch.

gcloud

Por ejemplo, para crear un trabajo en us-central1 que defina dos etiquetas personalizadas, una para cada uno de los dos elementos ejecutables del trabajo, sigue estos pasos:

Crea un archivo JSON que especifique los detalles de configuración del trabajo y los campos runnables.labels.

{
  "taskGroups": [
    {
      "taskSpec": {
        "runnables": [
          {
            "container": {
              "imageUri": "gcr.io/google-containers/busybox",
              "entrypoint": "/bin/sh",
              "commands": [
                "-c",
                "echo Hello from task ${BATCH_TASK_INDEX}!"
              ]
            },
            "labels": {
              "RUNNABLE1_LABEL_NAME1": "RUNNABLE1_LABEL_VALUE1"
            }
          },
          {
            "script": {
              "text": "echo Hello from task ${BATCH_TASK_INDEX}!"
            },
            "labels": {
              "RUNNABLE2_LABEL_NAME1": "RUNNABLE2_LABEL_VALUE1"
            }
          }
        ]
      }
    }
  ]
}

Haz los cambios siguientes:

RUNNABLE1_LABEL_NAME1: nombre de la etiqueta que se va a aplicar a la primera tarea ejecutable del trabajo.
RUNNABLE1_LABEL_VALUE1: el valor de la etiqueta que se va a aplicar a la primera tarea ejecutable del trabajo.
RUNNABLE2_LABEL_NAME1: nombre de la etiqueta que se va a aplicar al segundo ejecutable del trabajo.
RUNNABLE2_LABEL_VALUE1: el valor de la etiqueta que se va a aplicar al segundo ejecutable del trabajo.

Crea el trabajo en us-central1 con el comando gcloud batch jobs submit.
```
gcloud batch jobs submit example-job \
    --config=JSON_CONFIGURATION_FILE \
    --location=us-central1
```
Sustituye JSON_CONFIGURATION_FILE por la ruta al archivo JSON con los detalles de configuración del trabajo que has creado en el paso anterior.

API

Por ejemplo, para crear un trabajo en us-central1 que defina dos etiquetas personalizadas, una para cada uno de los dos elementos ejecutables del trabajo, haz una solicitud POST al método jobs.create y especifica los campos runnables.labels.

POST https://batch.googleapis.com/v1/projects/example-project/locations/us-central1/jobs?job_id=example-job

{
  "taskGroups": [
    {
      "taskSpec": {
        "runnables": [
          {
            "container": {
              "imageUri": "gcr.io/google-containers/busybox",
              "entrypoint": "/bin/sh",
              "commands": [
                "-c",
                "echo Hello from ${BATCH_TASK_INDEX}!"
              ]
            },
            "labels": {
              "RUNNABLE1_LABEL_NAME1": "RUNNABLE1_LABEL_VALUE1"
            }
          },
          {
            "script": {
              "text": "echo Hello from ${BATCH_TASK_INDEX}!"
            },
            "labels": {
              "RUNNABLE2_LABEL_NAME1": "RUNNABLE2_LABEL_VALUE1"
            }
          }
        ]
      }
    }
  ]
}

Haz los cambios siguientes:

RUNNABLE1_LABEL_NAME1: Nombre de la etiqueta que se va a aplicar al elemento ejecutable del primer trabajo.
RUNNABLE1_LABEL_VALUE1: valor de la etiqueta que se va a aplicar al elemento ejecutable del primer trabajo.
RUNNABLE2_LABEL_NAME1: nombre de la etiqueta que se va a aplicar al elemento ejecutable del segundo trabajo.
RUNNABLE2_LABEL_VALUE1: valor de la etiqueta que se va a aplicar al elemento ejecutable del segundo trabajo.

Java


import com.google.cloud.batch.v1.BatchServiceClient;
import com.google.cloud.batch.v1.ComputeResource;
import com.google.cloud.batch.v1.CreateJobRequest;
import com.google.cloud.batch.v1.Job;
import com.google.cloud.batch.v1.LogsPolicy;
import com.google.cloud.batch.v1.Runnable;
import com.google.cloud.batch.v1.TaskGroup;
import com.google.cloud.batch.v1.TaskSpec;
import com.google.protobuf.Duration;
import java.io.IOException;
import java.util.concurrent.ExecutionException;
import java.util.concurrent.TimeUnit;
import java.util.concurrent.TimeoutException;

public class CreateBatchRunnableLabel {
  public static void main(String[] args)
      throws IOException, ExecutionException, InterruptedException, TimeoutException {
    // TODO(developer): Replace these variables before running the sample.
    // Project ID or project number of the Google Cloud project you want to use.
    String projectId = "YOUR_PROJECT_ID";
    // Name of the region you want to use to run the job. Regions that are
    // available for Batch are listed on: https://cloud.google.com/batch/docs/get-started#locations
    String region = "us-central1";
    // The name of the job that will be created.
    // It needs to be unique for each project and region pair.
    String jobName = "example-job";
    // Name of the label1 to be applied for your Job.
    String labelName1 = "RUNNABLE_LABEL_NAME1";
    // Value for the label1 to be applied for your Job.
    String labelValue1 = "RUNNABLE_LABEL_VALUE1";
    // Name of the label2 to be applied for your Job.
    String labelName2 = "RUNNABLE_LABEL_NAME2";
    // Value for the label2 to be applied for your Job.
    String labelValue2 = "RUNNABLE_LABEL_VALUE2";

    createBatchRunnableLabel(projectId, region, jobName, labelName1,
        labelValue1, labelName2, labelValue2);
  }

  // Creates a job with labels defined in the labels field
  // for a runnable. The labels are only applied to that runnable.
  // In Batch, a runnable represents a single task or unit of work within a job.
  // It can be a container (like a Docker image) or a script.
  public static Job createBatchRunnableLabel(String projectId, String region, String jobName,
                   String labelName1, String labelValue1, String labelName2, String labelValue2)
      throws IOException, ExecutionException, InterruptedException, TimeoutException {
    // Initialize client that will be used to send requests. This client only needs to be created
    // once, and can be reused for multiple requests.
    try (BatchServiceClient batchServiceClient = BatchServiceClient.create()) {

      // Define what will be done as part of the job.
      Runnable runnable =
          Runnable.newBuilder()
              .setContainer(
                  Runnable.Container.newBuilder()
                      .setImageUri("gcr.io/google-containers/busybox")
                      .setEntrypoint("/bin/sh")
                      .addCommands("-c")
                      .addCommands(
                          "echo Hello world! This is task ${BATCH_TASK_INDEX}. "
                              + "This job has a total of ${BATCH_TASK_COUNT} tasks.")
                      .build())
              // Label and its value to be applied to the container
              // that processes data from a specific region.
              .putLabels(labelName1, labelValue1)
              .setScript(Runnable.Script.newBuilder()
              .setText("echo Hello world! This is task ${BATCH_TASK_INDEX}. ").build())
              // Label and its value to be applied to the script
              // that performs some analysis on the processed data.
              .putLabels(labelName2, labelValue2)
              .build();

      // We can specify what resources are requested by each task.
      ComputeResource computeResource =
          ComputeResource.newBuilder()
              // In milliseconds per cpu-second. This means the task requires 50% of a single CPUs.
              .setCpuMilli(2000)
              // In MiB.
              .setMemoryMib(2000)
              .build();

      TaskSpec task =
          TaskSpec.newBuilder()
              // Jobs can be divided into tasks. In this case, we have only one task.
              .addRunnables(runnable)
              .setComputeResource(computeResource)
              .setMaxRetryCount(2)
              .setMaxRunDuration(Duration.newBuilder().setSeconds(3600).build())
              .build();

      // Tasks are grouped inside a job using TaskGroups.
      // Currently, it's possible to have only one task group.
      TaskGroup taskGroup = TaskGroup.newBuilder().setTaskCount(1).setTaskSpec(task).build();

      Job job =
          Job.newBuilder()
              .addTaskGroups(taskGroup)
              // We use Cloud Logging as it's an out of the box available option.
              .setLogsPolicy(LogsPolicy.newBuilder()
              .setDestination(LogsPolicy.Destination.CLOUD_LOGGING).build())
              .build();

      CreateJobRequest createJobRequest =
          CreateJobRequest.newBuilder()
              // The job's parent is the region in which the job will run for the specific project.
              .setParent(String.format("projects/%s/locations/%s", projectId, region))
              .setJob(job)
              .setJobId(jobName)
              .build();

      Job result =
          batchServiceClient
              .createJobCallable()
              .futureCall(createJobRequest)
              .get(5, TimeUnit.MINUTES);

      System.out.printf("Successfully created the job: %s", result.getName());

      return result;
    }
  }

}

Node.js

// Imports the Batch library
const batchLib = require('@google-cloud/batch');
const batch = batchLib.protos.google.cloud.batch.v1;

// Instantiates a client
const batchClient = new batchLib.v1.BatchServiceClient();

/**
 * TODO(developer): Update these variables before running the sample.
 */
// Project ID or project number of the Google Cloud project you want to use.
const projectId = await batchClient.getProjectId();
// Name of the region you want to use to run the job. Regions that are
// available for Batch are listed on: https://cloud.google.com/batch/docs/get-started#locations
const region = 'us-central1';
// The name of the job that will be created.
// It needs to be unique for each project and region pair.
const jobName = 'example-job';
// Name of the label1 to be applied for your Job.
const labelName1 = 'RUNNABLE_LABEL_NAME1';
// Value for the label1 to be applied for your Job.
const labelValue1 = 'RUNNABLE_LABEL_VALUE1';
// Name of the label2 to be applied for your Job.
const labelName2 = 'RUNNABLE_LABEL_NAME2';
// Value for the label2 to be applied for your Job.
const labelValue2 = 'RUNNABLE_LABEL_VALUE2';

const container = new batch.Runnable.Container({
  imageUri: 'gcr.io/google-containers/busybox',
  entrypoint: '/bin/sh',
  commands: ['-c', 'echo Hello world! This is task ${BATCH_TASK_INDEX}.'],
});

const script = new batch.Runnable.Script({
  commands: ['-c', 'echo Hello world! This is task ${BATCH_TASK_INDEX}.'],
});

const runnable1 = new batch.Runnable({
  container,
  // Label and its value to be applied to the container
  // that processes data from a specific region.
  labels: {
    [labelName1]: labelValue1,
  },
});

const runnable2 = new batch.Runnable({
  script,
  // Label and its value to be applied to the script
  // that performs some analysis on the processed data.
  labels: {
    [labelName2]: labelValue2,
  },
});

// Specify what resources are requested by each task.
const computeResource = new batch.ComputeResource({
  // In milliseconds per cpu-second. This means the task requires 50% of a single CPUs.
  cpuMilli: 500,
  // In MiB.
  memoryMib: 16,
});

const task = new batch.TaskSpec({
  runnables: [runnable1, runnable2],
  computeResource,
  maxRetryCount: 2,
  maxRunDuration: {seconds: 3600},
});

// Tasks are grouped inside a job using TaskGroups.
const group = new batch.TaskGroup({
  taskCount: 3,
  taskSpec: task,
});

const job = new batch.Job({
  name: jobName,
  taskGroups: [group],
  // We use Cloud Logging as it's an option available out of the box
  logsPolicy: new batch.LogsPolicy({
    destination: batch.LogsPolicy.Destination.CLOUD_LOGGING,
  }),
});

// The job's parent is the project and region in which the job will run
const parent = `projects/${projectId}/locations/${region}`;

async function callCreateBatchLabelsRunnable() {
  // Construct request
  const request = {
    parent,
    jobId: jobName,
    job,
  };

  // Run request
  const [response] = await batchClient.createJob(request);
  console.log(JSON.stringify(response));
}

await callCreateBatchLabelsRunnable();

Python

from google.cloud import batch_v1


def create_job_with_custom_runnables_labels(
    project_id: str,
    region: str,
    job_name: str,
    labels: dict,
) -> batch_v1.Job:
    """
    This method creates a Batch job with custom labels for runnable.
    Args:
        project_id (str): project ID or project number of the Cloud project you want to use.
        region (str): name of the region you want to use to run the job. Regions that are
            available for Batch are listed on: https://cloud.google.com/batch/docs/locations
        job_name (str): the name of the job that will be created.
        labels (dict): a dictionary of key-value pairs that will be used as labels
            E.g., {"label_key1": "label_value2"}
    Returns:
        batch_v1.Job: The created Batch job object containing configuration details.
    """
    client = batch_v1.BatchServiceClient()

    runnable = batch_v1.Runnable()
    runnable.display_name = "Script 1"
    runnable.script = batch_v1.Runnable.Script()
    runnable.script.text = "echo Hello world from Script 1 for task ${BATCH_TASK_INDEX}"
    # Add custom labels to the first runnable
    runnable.labels = labels

    # Create a task specification and assign the runnable and volume to it
    task = batch_v1.TaskSpec()
    task.runnables = [runnable]

    # Specify what resources are requested by each task.
    resources = batch_v1.ComputeResource()
    resources.cpu_milli = 2000  # in milliseconds per cpu-second. This means the task requires 2 whole CPUs.
    resources.memory_mib = 16  # in MiB
    task.compute_resource = resources

    task.max_retry_count = 2
    task.max_run_duration = "3600s"

    # Create a task group and assign the task specification to it
    group = batch_v1.TaskGroup()
    group.task_count = 3
    group.task_spec = task

    # Policies are used to define on what kind of virtual machines the tasks will run on.
    # In this case, we tell the system to use "e2-standard-4" machine type.
    # Read more about machine types here: https://cloud.google.com/compute/docs/machine-types
    policy = batch_v1.AllocationPolicy.InstancePolicy()
    policy.machine_type = "e2-standard-4"
    instances = batch_v1.AllocationPolicy.InstancePolicyOrTemplate()
    instances.policy = policy
    allocation_policy = batch_v1.AllocationPolicy()
    allocation_policy.instances = [instances]

    # Create the job and assign the task group and allocation policy to it
    job = batch_v1.Job()
    job.task_groups = [group]
    job.allocation_policy = allocation_policy

    # We use Cloud Logging as it's an out of the box available option
    job.logs_policy = batch_v1.LogsPolicy()
    job.logs_policy.destination = batch_v1.LogsPolicy.Destination.CLOUD_LOGGING

    # Create the job request and set the job and job ID
    create_request = batch_v1.CreateJobRequest()
    create_request.job = job
    create_request.job_id = job_name
    # The job's parent is the region in which the job will run
    create_request.parent = f"projects/{project_id}/locations/{region}"

    return client.create_job(create_request)

Siguientes pasos

Usa etiquetas como filtros cuando hagas lo siguiente:
Consulta cómo eliminar trabajos.

Organizar recursos con etiquetas Organízate con las colecciones Guarda y clasifica el contenido según tus preferencias.

Antes de empezar

Restricciones

Etiquetas predefinidas

Definir etiquetas personalizadas

Definir etiquetas personalizadas para el trabajo y sus recursos

gcloud

API

Java

Node.js

Python

Definir etiquetas personalizadas para el trabajo

gcloud

API

Java

Node.js

Python

Definir etiquetas personalizadas para elementos ejecutables

gcloud

API

Java

Node.js

Python

Siguientes pasos

Organizar recursos con etiquetas